To assess the prevalence of vitamin D deficiency in healthy postmenopausal women with normal sun exposure but without vitamin D fortification in their diets. We studied 90 healthy ambulatory women who were residents of Santiago, Chile (latitude 33 degrees S); 30 were premenopausal (32.6 +/- 7.4 y), and 60 were postmenopausal (63.7 +/- 9.7 y). Half of the women were studied during the winter and the other half during the following summer. Each provided a fasting blood sample to measure biochemical parameters, parathyroid hormone, and 25-hydroxyvitamin D and completed a questionnaire to estimate sunlight exposure. A first morning urine sample was collected in postmenopausal women to measure deoxypyridinoline. Various cutoff points of 25-hydroxyvitamin D were used to assess the prevalence of vitamin D deficiency ( 0.05). In postmenopausal women, serum 25-hydroxyvitamin D was less than 9 ng/mL in 12%, less than 15 ng/mL in 40%, and less than 20 ng/mL in 60%, compared with 0%, 13%, and 27%, respectively, in premenopausal women. Deoxypyridinoline was 75% higher during winter than summer (9.8 +/- 2.5 vs 5.6 +/- 1.4 nmol/mmol creatinine, P < 0.0001). Vitamin D deficiency is very common in Chilean healthy postmenopausal women with normal sun exposure but without vitamin D fortification in their diets. This finding is associated with higher bone resorption during winter time and emphasizes the need to increase vitamin D intake in healthy postmenopausal women.

We review some aspects of nonparametric Bayesian data analysis with discrete random probability measures.We focus on the class of species sampling models (SSMs).We critically investigate the common use of the Dirichlet process (DP) prior as a default SSM choice. We discuss alternative prior specifications from a theoretical, computational and data analysis perspective. We conclude with a recommendation to consider SSM priors beyond the special case of the DP prior, and make specific recommendations on how different choices can be used to reflect prior information and how they impact the desired inference. We show the required changes in the posterior simulation schemes, and argue that the additional generality can be achieved without additional computational effort.

Shoulder pain is one of the most common musculoskeletal conditions, and for people over 40 years old, it represents the musculoskeletal pain with the greatest impact on quality of life. Psychological factors, such as fear-avoidance beliefs, are associated with musculoskeletal pain, and several studies suggest that they can influence various treatment outcomes. Our objective was to explore the cross-sectional association between fear-avoidance beliefs and shoulder pain intensity and disability in subjects with chronic shoulder pain. A cross-sectional study was conducted, and 208 participants with chronic unilateral subacromial shoulder pain were recruited. The shoulder pain and disability index assessed pain intensity and disability. The Spanish fear-avoidance components scale assessed the presence of fear-avoidance beliefs. The association between fear-avoidance beliefs and pain intensity and disability was analyzed by means of multiple linear regression models and proportional odds models, reporting odds ratios and 95% confidence intervals. Shoulder and pain disability scores were significantly associated with fear-avoidance beliefs (p < 0.0001, adjusted R-square 0.93, multiple linear regression). There was no evidence of an association between sex and age in this study. The regression coefficient for shoulder pain intensity and disability score was 0.67446. The proportional odds model showed an odds ratio of 1.39 (1.29–1.50) for shoulder pain intensity and disability total score. This study suggests that greater levels of fear-avoidance beliefs are associated with greater levels of shoulder pain and disability in adults with chronic shoulder pain.